Axis 2: Decision support made in complex systems

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Cahiers du GERAD

1373 results — page 1 of 69

This paper addresses the limitations of current satellite payload architectures, which are predominantly hardware-driven and lack the flexibility to adapt to...

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This paper tackles a complex variant of the unit commitment (UC) problem at Hydro-Quebec, referred to as the transient stability constrained unit commitmen...

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This work introduces solar, a collection of ten optimization problem instances for benchmarking blackbox optimization solvers. The instances present differ...

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The aim of this paper is to analyze the effect of adaptive investments on international environmental agreements (IEAs) focused on reducing greenhouse gas ...

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Integer (linear) programs are a standard way of formalizing a vast array of optimization problems in industry, services, management, science, and technology....

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Heterogeneous datasets emerge in various machine learning or optimization applications that feature different data sources, various data types and complex re...

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Randomized algorithms have proven to perform well on a large class of numerical linear algebra problems. Their theoretical analysis is critical to provide gu...

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Augmented Lagrangian (AL) methods are a well known class of algorithms for solving constrained optimization problems. They have been extended to the solution...

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Transit authorities are rapidly replacing conventional buses with electric ones because of the increasing concerns about air quality, greenhouse gas emission...

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Cellular solids are structures which have applications in mechanical engineering to make lightweight structures and heat exchangers, in biomedical engineer...

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This paper describes a planning problem faced by a fast-growing petroleum company in West Africa. The problem is a complex variant of the petrol station repl...

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Efficiently solving a vehicle routing problem (\(\mathcal{VRP}\)) in a practical runtime is a critical challenge for delivery management companies. This pa...

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This poster conceptually lays out recent advances in trustworthy machine learning (ML) that are of great interest for power systems applications like virtu...

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The truck loading and inventory routing problems are the two most important decisions made by companies replenishing petrol stations. This paper investigates...

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We develop a worst-case evaluation complexity bound for trust-region methods in the presence of unbounded Hessian approximations. We use the algorithm of Ar...

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The purpose of the present note is to bring clarifications to certain concepts and surrounding notation of Aravkin et al. (2022). All results therein contin...

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We develop a trust-region method for minimizing the sum of a smooth term \(f\) and a nonsmooth term \(h\), both of which can be nonconvex. Each iteratio...

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We develop an interior-point method for nonsmooth regularized bound-constrained optimization problems. Our method consists of iteratively solving a sequence...

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In this work, we study a class of two-player deterministic finite-horizon difference games with coupled inequality constraints, where both players have two t...

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The fine-tuning of Large Language Models (LLMs) has enabled them to recently achieve milestones in natural language processing applications. The emergenc...

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